Core Concepts: Encryption¶
Architecture Overview¶
The AIDDDMAP encryption system is built on a modular architecture that supports multiple encryption modes and provides extensive customization options. The system is designed to be secure, performant, and flexible while maintaining compatibility with various data types and use cases.
Key Components¶
1. Encryption Handlers¶
AgentEncryptionHandler¶
- Primary interface for agent-level encryption
- Manages encryption mode selection
- Handles data transformation and processing
- Integrates with the UADM for agent coordination
FHEHandler¶
- Implements Fully Homomorphic Encryption
- Uses Microsoft SEAL library
- Supports BFV and CKKS schemes
- Provides matrix operations and noise management
- Includes hardware acceleration support
ZKHandler¶
- Manages Zero-Knowledge proof generation and verification
- Supports multiple proof types
- Integrates with libsnark via WebAssembly
- Includes post-quantum secure schemes
- Features GPU-accelerated constraint processing
2. Post-Quantum Components¶
Kyber Implementation¶
- Key encapsulation mechanism
- Lattice-based security
- Configurable security levels
- Hardware-optimized operations
Dilithium Integration¶
- Digital signature scheme
- Post-quantum secure signatures
- Efficient verification process
- Configurable parameters
SPHINCS+ Support¶
- Hash-based signatures
- Stateless operation
- Multi-layer tree structure
- Long-term security focus
3. Zero-Knowledge Virtual Machine¶
Architecture¶
- Stack-based execution model
- Memory management system
- Instruction set processor
- Circuit execution engine
Features¶
- Instruction set support (LOAD, MUL, EQ)
- Memory limit enforcement
- Program counter tracking
- Circuit-to-instruction conversion
- Constraint verification
- Performance optimization
4. Circuit Optimization¶
GPU Acceleration¶
- WebGL-based processing
- Shader computation support
- Batch processing capability
- Memory optimization
- Parallel execution
- Performance monitoring
Optimization Levels¶
- Basic: Common term merging, redundancy elimination
- Aggressive: Parallel processing, GPU acceleration
Data Flow¶
1. Encryption Process¶
2. ZK Proof Generation¶
3. Post-Quantum Operations¶
Integration Points¶
1. Agent Integration¶
- Direct integration with agent lifecycle
- Automatic mode selection
- Performance monitoring
- Error handling and recovery
2. UADM Integration¶
- Centralized management
- Cross-agent coordination
- Resource allocation
- Performance optimization
3. Hardware Integration¶
- GPU acceleration support
- Memory optimization
- Parallel processing
- Hardware-specific optimizations
Security Considerations¶
1. Key Management¶
- Secure key generation
- Regular rotation schedule
- Backup procedures
- Access control implementation
2. Performance vs Security¶
- Configurable security levels
- Performance optimization options
- Resource usage monitoring
- Error handling strategies
3. Post-Quantum Security¶
- Algorithm selection
- Parameter configuration
- Key size management
- Future-proofing strategies
Best Practices¶
1. Mode Selection¶
- Choose appropriate encryption mode based on use case
- Consider performance requirements
- Evaluate security needs
- Account for data characteristics
2. Performance Optimization¶
- Enable GPU acceleration when available
- Use appropriate batch sizes
- Monitor resource usage
- Implement proper error handling
3. Security Implementation¶
- Regular security audits
- Proper access controls
- System monitoring
- Error logging and analysis
Future Considerations¶
1. Planned Enhancements¶
- Advanced circuit optimization
- Extended ZKVM capabilities
- Improved post-quantum schemes
- Enhanced GPU utilization
2. Scalability¶
- Improved parallel processing
- Enhanced memory management
- Advanced batch operations
- Hardware acceleration
3. Security Updates¶
- New proof systems
- Advanced optimization techniques
- Extended post-quantum support
- Improved monitoring tools